NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) vs QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB)

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NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) is faster in the only like-for-like comparison (largest gap: speech-to-text, 1.09×).

	NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB)	QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB)
Best speech-to-text	49327 FPS A undated	45408 FPS A undated
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	1 of 7	1 of 7

Best published speech-to-text result per platform (may be from different like-for-like groups — see data). n/a = not published; never estimated.

Show data — all workloads, sources and like-for-like groups

object detection

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No published object detection results for NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) or QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

instance segmentation

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No published instance segmentation results for NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) or QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

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No published pose estimation results for NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) or QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

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No published image classification results for NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) or QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

semantic segmentation

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No published semantic segmentation results for NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) or QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

speech-to-text

✓ Like-for-like: model-size class unknown, batch unknown (size or batch not stated by source — unverified). Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB)	49327 FPS throughput_offline · b=unknown	MLPerf whisper fp16 · TensorRT 10.14, CUDA 13.1 · unknown	A	unknown power n/a no power published	MLPerf Inference v6.0 (closed, datacenter) ID 6.0-0040 undated
QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB)	45408 FPS throughput_offline · b=unknown	MLPerf whisper fp16 · TensorRT 10.14, CUDA 13.1, cuDNN 9.17, TensorRT-LLM feat/1.2-mlpinf, NVIDIA Dynamo mlperf-v6.0-dynamo-v0.8.0, vLLM CentM · unknown	A	unknown power n/a no power published	MLPerf Inference v6.1 (closed, datacenter) ID D75H-10U_B300-270GBx8_TRT undated

LLM generation

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No published LLM generation results for NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB) or QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

How to read these numbers

Every number is labelled. Confidence: A MLPerf closed, audited · B documented third-party method · C community / review · D vendor-published, not independently verified · E estimate. Power basis: measured with the result · spec vendor spec/envelope · power n/a not published.

Machine-readable: /find.json (see llms.txt); full tables are in “Show data”. Confidence grades: A audited MLPerf closed · B documented third-party · C community · D vendor-published · E estimate. Unknown values are shown as unknown, never estimated. Generated 2026-10-16 from public sources.